Search results

1 – 10 of 324
To view the access options for this content please click here
Article
Publication date: 11 September 2017

Rudolf Espada, Armando Apan and Kevin McDougall

The purpose of this paper was to develop an integrated framework for assessing the flood risk and climate adaptation capacity of an urban area and its critical…

Abstract

Purpose

The purpose of this paper was to develop an integrated framework for assessing the flood risk and climate adaptation capacity of an urban area and its critical infrastructures to help address flood risk management issues and identify climate adaptation strategies.

Design/methodology/approach

Using the January 2011 flood in the core suburbs of Brisbane City, Queensland, Australia, various spatial analytical tools (i.e. digital elevation modeling and urban morphological characterization with 3D analysis, spatial analysis with fuzzy logic, proximity analysis, line statistics, quadrat analysis, collect events analysis, spatial autocorrelation techniques with global Moran’s I and local Moran’s I, inverse distance weight method, and hot spot analysis) were implemented to transform and standardize hazard, vulnerability, and exposure indicating variables. The issue on the sufficiency of indicating variables was addressed using the topological cluster analysis of a two-dimension self-organizing neural network (SONN) structured with 100 neurons and trained by 200 epochs. Furthermore, the suitability of flood risk modeling was addressed by aggregating the indicating variables with weighted overlay and modified fuzzy gamma overlay operations using the Bayesian joint conditional probability weights. Variable weights were assigned to address the limitations of normative (equal weights) and deductive (expert judgment) approaches. Applying geographic information system (GIS) and appropriate equations, the flood risk and climate adaptation capacity indices of the study area were calculated and corresponding maps were generated.

Findings

The analyses showed that on the average, 36 (approximately 813 ha) and 14 per cent (approximately 316 ha) of the study area were exposed to very high flood risk and low adaptation capacity, respectively. In total, 93 per cent of the study area revealed negative adaptation capacity metrics (i.e. minimum of −23 to <0), which implies that the socio-economic resources in the area are not enough to increase climate resilience of the urban community (i.e. Brisbane City) and its critical infrastructures.

Research limitations/implications

While the framework in this study was obtained through a robust approach, the following are the research limitations and recommended for further examination: analyzing and incorporating the impacts of economic growth; population growth; technological advancement; climate and environmental disturbances; and climate change; and applying the framework in assessing the risks to natural environments such as in agricultural areas, forest protection and production areas, biodiversity conservation areas, natural heritage sites, watersheds or river basins, parks and recreation areas, coastal regions, etc.

Practical implications

This study provides a tool for high level analyses and identifies adaptation strategies to enable urban communities and critical infrastructure industries to better prepare and mitigate future flood events. The disaster risk reduction measures and climate adaptation strategies to increase urban community and critical infrastructure resilience were identified in this study. These include mitigation on areas of low flood risk or very high climate adaptation capacity; mitigation to preparedness on areas of moderate flood risk and high climate adaptation capacity; mitigation to response on areas of high flood risk and moderate climate adaptation capacity; and mitigation to recovery on areas of very high flood risk and low climate adaptation capacity. The implications of integrating disaster risk reduction and climate adaptation strategies were further examined.

Originality/value

The newly developed spatially explicit analytical technique, identified in this study as the Flood Risk-Adaptation Capacity Index-Adaptation Strategies (FRACIAS) Linkage/Integrated Model, allows the integration of flood risk and climate adaptation assessments which had been treated separately in the past. By applying the FRACIAS linkage/integrated model in the context of flood risk and climate adaptation capacity assessments, the authors established a framework for enhancing measures and adaptation strategies to increase urban community and critical infrastructure resilience to flood risk and climate-related events.

Details

International Journal of Disaster Resilience in the Built Environment, vol. 8 no. 4
Type: Research Article
ISSN: 1759-5908

Keywords

To view the access options for this content please click here
Article
Publication date: 16 July 2021

Zhao Yaoteng and Li Xin

The purpose of this paper is to explore the sustainable development strategy of green finance under the background of big data.

Abstract

Purpose

The purpose of this paper is to explore the sustainable development strategy of green finance under the background of big data.

Design/methodology/approach

From the perspective of big data, this paper uses quantitative and qualitative analysis methods to judge the correlation among green finance, environmental supervision and financial supervision. Green finance gives the entropy method to calculate the score of green finance and environmental regulation, and establishes the spatial lag model under the double fixed effects of time and space.

Findings

Spatial autocorrelation test shows that economic spatial weight matrix has obvious spatial effect on green innovation. Through the model selection test, the space lag model with fixed time and space is selected. The regression coefficients of green finance, environmental regulation and their interaction are 0.1598, 0.0541 and 0.1763, respectively, which significantly promote green innovation. The regression coefficients of openness, higher education level and per capita GDP are 0.0361, 0.0819 and 0.0686, respectively, which can significantly promote green innovation.

Originality/value

In view of the current situation of large-scale application of big data technology in green innovation of domestic energy-saving and environmental protection enterprises, this paper establishes a fixed time lag evaluation model of green innovation. M-test statistics show that the original hypothesis with no obvious spatial effect is rejected.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

To view the access options for this content please click here
Article
Publication date: 3 October 2016

David McIlhatton, William McGreal, Paloma Taltavul de la Paz and Alastair Adair

There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the…

Abstract

Purpose

There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime.

Design/methodology/approach

The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data.

Findings

The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables.

Originality/value

The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.

Details

International Journal of Housing Markets and Analysis, vol. 9 no. 4
Type: Research Article
ISSN: 1753-8270

Keywords

To view the access options for this content please click here
Article
Publication date: 27 May 2021

Ying Song, Yi Zhang, Yafei Wang, Bowen Zhang and Jiafu Su

Taking 30 provincial samples from 2001 to 2017 in mainland China as the research objects, this paper aims to evaluate the impact and effects of foreign direct investment…

Abstract

Purpose

Taking 30 provincial samples from 2001 to 2017 in mainland China as the research objects, this paper aims to evaluate the impact and effects of foreign direct investment (FDI) on the urban–rural income gap and reveals heterogeneity across regions.

Design/methodology/approach

Firstly, the Theil index is used to measure the income gap between 30 provinces in mainland China from 2001 to 2017, then the spatial econometric model is used to empirically test the impact of foreign direct investment on China’s urban–rural income gap and its heterogeneity across regions. Finally, a robustness test is performed.

Findings

The results show that there is a significant inverted U-shaped relationship between FDI and the urban–rural income gap in China. That is, FDI expands the urban–rural income gap in the short term and helps to converge it in the long term. In the eastern region, FDI has a convergence effect on the urban–rural income gap in the short term, which increases the long term. However, in the central and western regions, the relationship between FDI and urban–rural income gap has a weak inverted U shape.

Originality/value

By assessing the impact of FDI on the urban–rural income gap, this work provides decision-making support for China and other developing countries to improve investment policies and income distribution policies.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

To view the access options for this content please click here
Article
Publication date: 15 February 2021

Richard Adeleke, Opeyemi Alabede, Tolulope Osayomi and Ayodeji Iyanda

Globally, corruption has been identified as a major problem. Even though corruption is widespread, it varies in magnitude, types and consequences. In Nigeria, corruption…

Abstract

Purpose

Globally, corruption has been identified as a major problem. Even though corruption is widespread, it varies in magnitude, types and consequences. In Nigeria, corruption is endemic, and it is responsible for the many socioeconomic problems in the country. Hence, the study aims to determine the patterns and state level correlations of corruption in Nigeria.

Design/methodology/approach

Data for this study were sourced from the National Bureau of Statistics and other official sources and were analyzed with Global Moran’s I, Local Moran’s I and multivariate step-wise regression.

Findings

This study’s findings revealed significant clustering of corruption in the country with Rivers States as the only hotspot (I = 0.068; z = 2.524; p < 0.05), while domestic debt and market size were the state level significant predictors.

Research limitations/implications

Only bribery as a form of corruption was examined in this study, more studies are needed on the predictors of other forms of corruption.

Practical implications

This study recommends increased market competition through investment grants, subsidies and tax incentives to facilitate trade interactions among Nigerians, which can lead to exchange of cultural norms that discourage corruption. It is also advocated that domestic debt must be effectively and efficiently channelled towards economic development which in the long run will have a positive impact on the socio-economic well-being of the citizens as well as drive down corrupt practices.

Originality/value

Although the causes of corruption have received considerable attention in the literature, little is known on the geographical distribution and the effect of market size and domestic debt on corruption in Nigeria.

Details

Journal of Financial Crime, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1359-0790

Keywords

Content available
Article
Publication date: 26 September 2019

Yongjing Wang, Qingxin Lan, Feng Jiang and Chaofan Chen

As the contradiction between economic development, resource and environment has become increasingly prominent, low-carbon competitiveness has received worldwide focus…

Abstract

Purpose

As the contradiction between economic development, resource and environment has become increasingly prominent, low-carbon competitiveness has received worldwide focus. This study aims to examine low-carbon competitiveness in 31 provinces (cities and regions) of China.

Design/methodology/approach

An evaluation index system for low-carbon competitiveness in China has been constructed, which is composed of 25 economic, social, environmental and policy indicators. To study the state of low-carbon competitiveness and resistance to China’ development of low-carbon competitiveness, this study uses a combination of the catastrophe progression model, the spatial autocorrelation model and the barrier method.

Findings

China’ low-carbon competitiveness gradually decreases from coastal to inland areas: the Tibet and Ningxia Hui autonomous regions are the least competitive regions, while the Shandong and Jiangsu provinces are the most competitive areas. The spatial correlation of the 31 provinces’ low-carbon competitiveness is very low and lacks regional cooperation. This study finds that the proportion of a region’ wetland area, the proportion of tertiary industries represented in its GDP and afforestation areas are the main factors in the development of low-carbon competitiveness. China should become the leader of carbon competitiveness by playing the leading role in the Eastern Region, optimizing the industrial structure, improving government supervision and strengthening environmental protection.

Originality/value

The paper provides a quantitative reference for evaluating China’ low-carbon competitiveness, which is beneficial for environmental policymaking. In addition, the evaluation and analysis methods offer relevant implications for developing countries.

Details

International Journal of Climate Change Strategies and Management, vol. 12 no. 1
Type: Research Article
ISSN: 1756-8692

Keywords

To view the access options for this content please click here
Article
Publication date: 18 May 2015

Vigdis Boasson and Emil Boasson

The purpose of this paper is to examine the role of geographic location of research-intensive firms in the ability to generate new research and products, which…

Abstract

Purpose

The purpose of this paper is to examine the role of geographic location of research-intensive firms in the ability to generate new research and products, which consequently affects firm value.

Design/methodology/approach

The authors conduct the empirical study following a three-step process. First, if pharmaceutical firms are more likely to cite the patents of other firms and other innovators that are nearby, as opposed to firms and other innovators that are far away, then location (i.e. close proximity) is likely important when it comes to the ability to learn and to use the knowledge being generated by other innovators. The authors employ a “geographic information systems” (GIS) and geo-code each pair of citing and cited patents. In addition, the authors utilize spatial statistics such as Moran’s I to analyze the spatial clustering pattern of patent citations and knowledge flows. Next, the authors measure the pharmaceutical companies’ ability to generate useful patents as a function of the amount of innovation and industrial activity that is occurring close to them. Finally, the authors test whether a firm’s location relates to its firm value. Specifically, the authors model firm value as a function of its patents quality, but the authors also allow the firm’s patents quality to be a function of its location and locational attributes. In this way, the authors establish a link between location and firm value. Using a simultaneous system of equations, the authors find that location explains patent quality, which, in turn, explains firm value. In other words, there is a positive relationship between firm value, innovation and location.

Findings

In empirical tests using pharmaceutical firms and their patents, the authors first find that firms more often cite patents of other firms that are geographically closer to them than those firms that are farther away. The authors then find that a patent’s quality is a function of the firm’s near proximity to other knowledge-intensive institutions and activities. Finally, the authors find that because patent quality is a function of a firm’s geographic location, location consequently affects firm value.

Research limitations/implications

For knowledge-intensive firms, geographic location matters. More specifically, the authors contend that research-intensive firms are better able to use and to expand on existing knowledge when they are closer to other research-intensive enterprises. The implication is that firm value maximization involves a location factor.

Practical implications

The practical implication for investors is that investors should invest in those firms that are situated in a location that is rich in geographic innovation resources because those firms are more likely to generate more and higher quality patents or innovations.

Originality/value

The study is the first to establish the linkage among spatial knowledge diffusion, geographic drivers of innovation, and market valuation of the firm. The study is unique in that the authors not only present evidence on spatial knowledge flows by geo-coding the exact longitude and latitude location coordinates of citing and cited patens, but more importantly, the authors also identify geographic drivers of innovation, and examine their impacts on citation-weighted patent counts and knowledge stock. Finally, using a series of simultaneous equations, the authors show how geographic innovation resources positively affect citation-weighted patent stock and knowledge stock and consequently affect market value of the firm. Thus, the novel approach contributes not only to the literature that measures geographic localization of knowledge flow using patent citations, but also to the literature that examines the impact of geographic sources of innovations on patent outputs and patent quality and, thus on firm value for research-intensive firms.

Details

China Finance Review International, vol. 5 no. 2
Type: Research Article
ISSN: 2044-1398

Keywords

To view the access options for this content please click here
Article
Publication date: 10 August 2015

Maria Veronica Alderete

This paper aims to determine if there is a spatial dependence in the entrepreneurial activity among countries. The existence of a “digital proximity” could explain the…

Abstract

Purpose

This paper aims to determine if there is a spatial dependence in the entrepreneurial activity among countries. The existence of a “digital proximity” could explain the spatial pattern of entrepreneurship.

Design/methodology/approach

This question is empirically addressed by using a five-period, 2008-2012, panel data for 35 countries. A spatial fixed effects panel data model is estimated by using the total entrepreneurial activity published by the global entrepreneurship monitor as the dependent variable.

Findings

A significant negative influence of the digital proximity on the entrepreneurial activity is observed. Mobile broadband (MB) direct effect is positive while the indirect effect (the spatial spillovers) is negative, leading to a negative total effect on the total entrepreneurial activity. This result is contrary to non-spatial models’ results. Besides, a higher MB penetration in a country would lead to a competitive advantage fostering its opportunities for entrepreneurship, but reducing those of its neighbours’.

Originality/value

This paper examines the relationship between information and communication technology (ICT) and entrepreneurship, by introducing the spatial effects is the main contribution. This paper expands the scant literature on the ICT impact on entrepreneurship. Results obtained support policies towards enforcing innovation, education and reducing entry regulations for encouraging entrepreneurship. Meanwhile, MB policies could counteract the entrepreneurial policies’ results due to the spatial dependence.

Details

info, vol. 17 no. 5
Type: Research Article
ISSN: 1463-6697

Keywords

To view the access options for this content please click here
Article
Publication date: 14 May 2018

David Ansong, Chesworth Brittney Renwick, Moses Okumu, Eric Ansong and Cedrick Joseph Wabwire

The purpose of this paper is to examine the spatial patterns of gender inequality in junior high school enrollment and the educational resource investments associated with…

Abstract

Purpose

The purpose of this paper is to examine the spatial patterns of gender inequality in junior high school enrollment and the educational resource investments associated with the spatial trends.

Design/methodology/approach

The paper uses data on 170 districts in Ghana and hot spot analysis based on the Getis-Ord Gi statistic, linear regression, and geographically weighted regression to assess spatial variability in gender parity in junior high school enrollment and its association with resource allocation.

Findings

The results reveal rural-urban and north-south variability in gender parity. Results show that educational resources contribute to gender parity. At the national level, educational expenditure, and the number of classrooms, teachers, and available writing places have the strongest positive associations with girls’ enrollment. These relationships are spatially moderated, such that predominantly rural and Northern districts experience the most substantial benefits of educational investments.

Practical implications

The findings show that strategic allocation of infrastructure, financial, and human resources through local governments holds promise for a more impactful and sustainable educational development of all children, regardless of gender. Besides seeking solutions that address the lack of resources at the national level, there is a need for locally tailored efforts to remove the barriers to equitable distribution of educational resources across gender and socioeconomic groups.

Originality/value

This paper’s use of advanced spatial analysis techniques allows for in-depth examination of gender parity and investments in educational resources, and highlights the spatial nuances in how such investments predict gender disparities in junior high school enrollment. The findings speak to the need for targeted and localized efforts to address gender and geographical disparities in educational opportunities.

Details

Journal of Economic Studies, vol. 45 no. 2
Type: Research Article
ISSN: 0144-3585

Keywords

To view the access options for this content please click here
Article
Publication date: 28 May 2021

Lokender Prashad, Mili Dutta and Bishnu Mohan Dash

This study on spatial analysis of child labour in India is a macro level analysis on child labour using the census data, 2011 of Government of India. The population census…

Abstract

Purpose

This study on spatial analysis of child labour in India is a macro level analysis on child labour using the census data, 2011 of Government of India. The population census which is conducted once in 10 years only provides district level data on work-force distribution. The study has spatial analysis of child labour in the age group of 5–14 years in India. To assess the magnitude of the children in the labour force, district level data of Census 2011 has been used in the study. The study has made an attempt to identify the districts where there is high level of children in the labour force. This paper aims to estimate the magnitude and trends of children’s workforce participation using the census data as it is the only data base, which is available at the district level since 1961 onwards. The study has made an attempt to identify the clustering of child labour across districts in India and how child labour is clustered by different background characteristics.

Design/methodology/approach

The study has used ArcGIS software package, GeoDa software and local indicator of spatial association test.

Findings

The findings of study reveal that the proportion of rural, total fertility rate (TFR) and poverty headcount ratio is positively associated, whereas female literacy and the pupil-teacher ratio are negatively associated with child labour. It suggests that in the hot-spot areas and areas where there is a high prevalence of child labour, there is need to increase the teacher's number at the school level to improve the teacher-pupil ratio and also suggested to promote the female education, promote family planning practices to reduce TFR in those areas for reducing the incidences of child labour.

Research limitations/implications

The study also recommends that the incidences of child labour can be controlled by a comprehensive holistic action plan with the active participation of social workers.

Practical implications

The promulgation of effective legislation, active involvement of judiciary and police, political will, effective poverty alleviation and income generation programmes, sensitisation of parents, corporates and media can play effective role in mitigating the incidences of child labour in India. To achieve the sustainable development goals (SDGs) adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025.

Social implications

The study aims to achieve the SDGs adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025.

Originality/value

The study is purely original and there are no such studies in Indian context by using the latest software.

Details

Journal of Children's Services, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-6660

Keywords

1 – 10 of 324